code: def test_gradcheck(self, device):
      # generate input data
      batch_size, num_points, num_dims = 2, 3, 2
      points1 = torch.rand(
          batch_size,
          num_points,
          num_dims,
          device=device,
          dtype=torch.float64,
          requires_grad=True,
      )
      points2 = torch.rand(
          batch_size,
          num_points,
          num_dims,
          device=device,
          dtype=torch.float64,
      )
      Fm = utils.create_random_fundamental_matrix(batch_size).type_as(
          points2
      )
      assert gradcheck(
          epi.symmetrical_epipolar_distance,
          (points1, points2, Fm),
          raise_exception=True,
          fast_mode=True,
      )
  
imports: import torch
  from torch.autograd import gradcheck
  import kornia.geometry.epipolar
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 4 for calling the TestSymmetricalEpipolarDistance obj's underlying member method code with example usage: obj.test_gradcheck(device) without return types